IMPROVED FINGERPRINT COMPRESSION TECHNIQUE WITH DECIMATED MULTI-WAVELET COEFFICIENTS FOR LOW BIT RATES

N. R. Rema, P. Mythili
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Abstract

In this paper, a multi-wavelet transform with decimated frequency bands is proposed to be used in the Set Partitioning in Hierarchical Trees (SPIHT) algorithm to improve fingerprint image compression. Either shuffled or unshuffled multi-wavelets can be used for SPIHT algorithm. In both the cases, the quality of the compressed images at lower bit rates either remained the same or slightly improved compared to wavelets. To improve the performance at lower bit rates, a method which utilizes the decimated version of multi-wavelet for the initialization of lists in SPIHT algorithm is used. The multi-wavelet used for the proposed work is SA4 (Symmetric-Antisymmetric). The algorithm was tested and verified using NIST, Shivang Patel, NITGEN and other databases. An overall improvement in performance particularly at lower bit rates (0.01 to 0.09) compared to a multi-wavelet without decimation was obtained using this method. The improvement was 0.798dB, 0.857dB and 0.859dB for the images in NITGEN database for a multi-wavelet decimated by 2, 4 and 8 respectively. Similar performances were observed for other databases. It was further observed that the PSNR was highest when the multi-wavelet was decimated by a factor of 4.
改进的指纹压缩技术与抽取多小波系数为低比特率
本文提出了将抽取频带的多小波变换用于分层树集分割(SPIHT)算法中,以提高指纹图像的压缩性能。在SPIHT算法中可以使用洗刷或不洗刷的多小波。在这两种情况下,与小波相比,在较低比特率下压缩图像的质量要么保持不变,要么略有改善。为了提高在低比特率下的性能,采用了SPIHT算法中利用多小波的抽取版本进行列表初始化的方法。所提出的工作使用的多小波是SA4(对称-反对称)。使用NIST、shiang Patel、NITGEN等数据库对算法进行了测试和验证。与没有抽取的多小波相比,在较低的比特率(0.01至0.09)下,使用该方法获得了性能的总体改进。对NITGEN数据库中的多小波分别抽取2、4和8个小波后,图像的改进幅度分别为0.798dB、0.857dB和0.859dB。在其他数据库中也观察到类似的性能。进一步观察到,当多小波被抽取4倍时,PSNR最高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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